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Horizontal trajectory control of stratospheric airships in wind field using Q-learning algorithm

机译:Q学习算法风场中平流层飞艇的水平轨迹控制

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摘要

This paper proposes an adaptive horizontal trajectory control method for stratospheric airships in uncertain wind field using Q-learning algorithm. Firstly, horizontal trajectory control of the airships is decomposed into the target tracking, and the observation model of airships is constructed. Then, the Markov decision process (MDP) model of airships is established, in which the action strategy is determined by the wind direction, and a cerebellar model articulation controller (CMAC) neural network is designed to optimize the action strategy for each state. Finally, numerical simulations demonstrate that the proposed control method performs well stability and intelligent decision-making ability in the process of horizontal trajectory control for stratospheric airships. (C) 2020 Elsevier Masson SAS. All rights reserved.
机译:本文提出了一种使用Q学习算法在不确定风场中的平流层飞艇的自适应水平轨迹控制方法。首先,飞艇的水平轨迹控制被分解为目标跟踪,构建飞艇观测模型。然后,建立了Markov决策过程(MDP)的飞艇模型,其中由风向确定动作策略,并且设计了一个小脑模型铰接控制器(CMAC)神经网络以优化每个状态的动作策略。最后,数值模拟表明,所提出的控制方法在流程图飞艇水平轨迹控制过程中执行良好的稳定性和智能决策能力。 (c)2020 Elsevier Masson SAS。版权所有。

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